Evaluation of a fast implicit solvent model for molecular dynamics simulations

In silico exploration of CB2 receptor agonist in the management of neuroinflammatory conditions by pharmacophore modeling

Endocannabinoid system plays a pivotal role in controlling neuroinflammation, and modulating this system may not only aid in managing symptoms of neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, Multiple sclerosis, Epilepsy, Central and Peripheral neuropathic pain, but also, have the potential to target these diseases at an early-stage. In the present study, six different pharmacophore hypotheses were generated from Cannabidiol (CBD)-Cannabinoid Receptor subtype-2 (CB2) and then Zinc database was screened for identification of hit molecules. Identified 215 hit molecules were subjected to preliminary screening with ADMET and drug likeness properties, and about 48 molecules were found with no violations and toxicity properties. In molecular docking studies, six compounds showed better binding energy than CBD and β-caryophyllene (known inhibitor of CB2). These six molecules were designated as leads and subjected to re-docking with glide tool and Lead1 (ZINC000078815430) showed docking score of -9.877 kcal/mol, whereas CBD and β-caryophyllene showed score of -9.664 and -8.499 kcal/mol, respectively. Lead1 and CBD were evaluated for stability studies with Desmond tool by molecular dynamic simulation studies. Lead1 showed better stability than CBD in all studied parameters such as RMSD, RMSF, SSE, Rg, SASA, etc. In MM-GBSA free energy calculations, ΔGbinding energy of CB2-CBD complex and CB2-Lead1 were found to be -103.13±11.19 and -107.94±5.42 kcal/mol, respectively. Six lead molecules stated in the study hold promise with respect to CBD agonistic activity for treating and/or managing chronic conditions and can be explored as an alternative for early-stage cure, which has not yet been experimentally explored.

Isolation and in silico investigation of cannflavins from Cannabis sativa leaves as potential anti-SARS-CoV-2 agents targeting the Papain-Like Protease

This study aimed to isolate and identify three prenylflavonoids (cannflavin A, B, and C) from Cannabis sativa leaves using different chromatographic techniques. The potential of the isolated compounds against SARS-CoV-2 was suggested through several in silico analysis. Structural similarity studies against nine co-crystallized ligands of SARS-CoV-2's proteins indicated the similarities of the isolated cannflavins with the SARS-CoV-2 Papain-Like Protease (PLP) ligand, Y95. Then, flexible allignment study confirmed this similarity. Docking experiments showed successful binding of all cannflavins within the active pocket of PLP, with energies comparable to Y95. Among them, cannflavin A demonstrated the most similar binding mode, while cannflavin C exhibited the best energy. Molecular dynamics (MD) simulations and MM-GPSA confirmed the accurate binding of cannflavin A to the PLP. In silico ADMET studies indicated favourable drug-like properties for all three compounds, suggesting their potential as anti-SARS-CoV-2 agents. Further In vitro and In vivo investigations are necessary to validate these findings and establish their efficacy and safety profiles.

In silico engineering and simulation of RNA interferences nanoplatforms for osteoporosis treating and bone healing promoting

Osteoporosis is a bone condition characterized by reduced bone mineral density (BMD), poor bone microarchitecture/mineralization, and/or diminished bone strength. This asymptomatic disorder typically goes untreated until it presents as a low-trauma fracture of the hip, spine, proximal humerus, pelvis, and/or wrist, requiring surgery. Utilizing RNA interference (RNAi) may be accomplished in a number of ways, one of which is by the use of very tiny RNA molecules called microRNAs (miRNAs) and small interfering RNAs (siRNAs). Several kinds of antagomirs and siRNAs are now being developed to prevent the detrimental effects of miRNAs. The goal of this study is to find new antagonists for miRNAs and siRNAs that target multiple genes in order to reduce osteoporosis and promote bone repair. Also, choosing the optimum nanocarriers to deliver these RNAis appropriately to the body could lighten up the research road. In this context, we employed gene ontology analysis to search across multiple datasets. Following data analysis, a systems biology approach was used to process it. A molecular dynamics (MD) simulation was used to explore the possibility of incorporating the suggested siRNAs and miRNA antagonists into polymeric bioresponsive nanocarriers for delivery purposes. Among the three nanocarriers tested [polyethylene glycol (PEG), polyethylenimine (PEI), and PEG-PEI copolymer], MD simulations show that the integration of PEG-PEI with has-mIR-146a-5p is the most stable (total energy = -372.84 kJ/mol, Gyration radius = 2.1084 nm), whereas PEI is an appropriate delivery carrier for has-mIR-7155. The findings of the systems biology and MD simulations indicate that the proposed RNAis might be given through bioresponsive nanocarriers to accelerate bone repair and osteoporosis treatment.

Computational Study on the Enzyme-Ligand Relationship between Cannabis Phytochemicals and Human Acetylcholinesterase: Implications in Alzheimer's Disease

Cannabis has shown promise in treating various neurological disorders, including Alzheimer's disease (AD). AD is a devastating neurodegenerative disorder that affects millions of people worldwide. Current treatments for AD are limited and are not very effective. This study investigated the enzyme-ligand relationship between nine active components of cannabis and human acetylcholinesterase (HuAChE) enzyme, which is significant in AD. Specifically, computational methods such as quantum mechanics, molecular docking, molecular dynamics, and free energy calculations were used to identify the cannabis phytochemicals with the highest HuAChE affinity and to understand the specific binding mechanisms involved. Our results showed that cannabichromene and cannabigerol were the cannabis phytochemicals with the highest affinity for HuAChE, with cannabichromene exhibiting the greatest binding energy. However, both substances showed lower affinity than that of the pharmaceutical drug donepezil. This study suggests that cannabichromene has a specific affinity for the peripheral anionic site (PAS) and acyl-binding pocket (ABP), while cannabigerol predominantly binds to PAS. Also, it was found that cannabichromene has a specific affinity for PAS and ABP, while cannabigerol predominantly binds to PAS. Our findings suggest that cannabichromene and cannabigerol are potential therapeutic agents, but further research is needed to validate their effectiveness. The specific binding mechanisms identified may also provide helpful information for the design of more effective cannabis-based drugs. Overall, this study provides valuable insights into the potential of cannabis-based drugs for treating neurological diseases.

Toward Accurate Coarse-Grained Simulations of Disordered Proteins and Their Dynamic Interactions

Intrinsically disordered proteins (IDPs) play crucial roles in cellular regulatory networks and are now recognized to often remain highly dynamic even in specific interactions and assemblies. Accurate description of these dynamic interactions is extremely challenging using atomistic simulations because of the prohibitive computational cost. Efficient coarse-grained approaches could offer an effective solution to overcome this bottleneck if they could provide an accurate description of key local and global properties of IDPs in both unbound and bound states. The recently developed hybrid-resolution (HyRes) protein model has been shown to be capable of providing a semiquantitative description of the secondary structure propensities of IDPs. Here, we show that greatly improved description of global structures and transient interactions can be achieved by introducing a solvent-accessible surface area-based implicit solvent term followed by reoptimization of effective interaction strengths. The new model, termed HyRes II, can semiquantitatively reproduce a wide range of local and global structural properties of a set of IDPs of various lengths and complexities. It can also distinguish the level of compaction between folded proteins and IDPs. In particular, applied to the disordered N-terminal transactivation domain (TAD) of tumor suppressor p53, HyRes II is able to recapitulate various nontrivial structural properties compared to experimental results, some of them to a level of accuracy that is almost comparable to results from atomistic explicit solvent simulations. Furthermore, we demonstrate that HyRes II can be used to simulate the dynamic interactions of TAD with the DNA-binding domain of p53, generating structural ensembles that are highly consistent with existing NMR data. We anticipate that HyRes II will provide an efficient and relatively reliable tool toward accurate coarse-grained simulations of dynamic protein interactions.

Fibrin protofibril packing and clot stability are enhanced by extended knob-hole interactions and catch-slip bonds

Fibrin polymerization involves thrombin-mediated exposure of knobs on one monomer that bind to holes available on another, leading to the formation of fibers. In silico evidence has suggested that the classical A:a knob-hole interaction is enhanced by surrounding residues not directly involved in the binding pocket of hole a, via noncovalent interactions with knob A. We assessed the importance of extended knob-hole interactions by performing biochemical, biophysical, and in silico modeling studies on recombinant human fibrinogen variants with mutations at residues responsible for the extended interactions. Three single fibrinogen variants, γD297N, γE323Q, and γK356Q, and a triple variant γDEK (γD297N/γE323Q/γK356Q) were produced in a CHO (Chinese Hamster Ovary) cell expression system. Longitudinal protofibril growth probed by atomic force microscopy was disrupted for γD297N and enhanced for the γK356Q mutation. Initial polymerization rates were reduced for all variants in turbidimetric studies. Laser scanning confocal microscopy showed that γDEK and γE323Q produced denser clots, whereas γD297N and γK356Q were similar to wild type. Scanning electron microscopy and light scattering studies showed that fiber thickness and protofibril packing of the fibers were reduced for all variants. Clot viscoelastic analysis showed that only γDEK was more readily deformable. In silico modeling suggested that most variants displayed only slip-bond dissociation kinetics compared with biphasic catch-slip kinetics characteristics of wild type. These data provide new evidence for the role of extended interactions in supporting the classical knob-hole bonds involving catch-slip behavior in fibrin formation, clot structure, and clot mechanics.

A topological refactoring design strategy yields highly stable granulopoietic proteins

Protein therapeutics frequently face major challenges, including complicated production, instability, poor solubility, and aggregation. De novo protein design can readily address these challenges. Here, we demonstrate the utility of a topological refactoring strategy to design novel granulopoietic proteins starting from the granulocyte-colony stimulating factor (G-CSF) structure. We change a protein fold by rearranging the sequence and optimising it towards the new fold. Testing four designs, we obtain two that possess nanomolar activity, the most active of which is highly thermostable and protease-resistant, and matches its designed structure to atomic accuracy. While the designs possess starkly different sequence and structure from the native G-CSF, they show specific activity in differentiating primary human haematopoietic stem cells into mature neutrophils. The designs also show significant and specific activity in vivo. Our topological refactoring approach is largely independent of sequence or structural context, and is therefore applicable to a wide range of protein targets.

Skokowa et al. reconstruct the fold of a granulopoietic cytokine, resulting in de novo, hyperstable, highly active proteins with therapeutic potential for treating several neutropenia disorders.

Physics-based modeling provides predictive understanding of selectively promiscuous substrate binding by Hsp70 chaperones

To help cells cope with protein misfolding and aggregation, Hsp70 molecular chaperones selectively bind a variety of sequences ("selective promiscuity"). Statistical analyses from substrate-derived peptide arrays reveal that DnaK, the E. coli Hsp70, binds to sequences containing three to five branched hydrophobic residues, although otherwise the specific amino acids can vary considerably. Several high-resolution structures of the substrate -binding domain (SBD) of DnaK bound to peptides reveal a highly conserved configuration of the bound substrate and further suggest that the substrate-binding cleft consists of five largely independent sites for interaction with five consecutive substrate residues. Importantly, both substrate backbone orientations (N- to C- and C- to N-) allow essentially the same backbone hydrogen-bonding and side-chain interactions with the chaperone. In order to rationalize these observations, we performed atomistic molecular dynamics simulations to sample the interactions of all 20 amino acid side chains in each of the five sites of the chaperone in the context of the conserved substrate backbone configurations. The resulting interaction energetics provide the basis set for deriving a predictive model that we call Paladin (Physics-based model of DnaK-Substrate Binding). Trained using available peptide array data, Paladin can distinguish binders and nonbinders of DnaK with accuracy comparable to existing predictors and further predicts the detailed configuration of the bound sequence. Tested using existing DnaK-peptide structures, Paladin correctly predicted the binding register in 10 out of 13 substrate sequences that bind in the N- to C- orientation, and the binding orientation in 16 out of 22 sequences. The physical basis of the Paladin model provides insight into the origins of how Hsp70s bind substrates with a balance of selectivity and promiscuity. The approach described here can be extended to other Hsp70s where extensive peptide array data is not available.

Systematic Development of Peptide Inhibitors Targeting the CXCL12/HMGB1 Interaction

During inflammatory reactions, the production and release of chemotactic factors guide the recruitment of selective leukocyte subpopulations. The alarmin HMGB1 and the chemokine CXCL12, both released in the microenvironment, can form a heterocomplex, which exclusively acts on the chemokine receptor CXCR4, enhancing cell migration, and in some pathological conditions such as rheumatoid arthritis exacerbates the immune response. An excessive cell influx at the inflammatory site can be diminished by disrupting the heterocomplex. Here, we report the computationally driven identification of the first peptide (HBP08) binding HMGB1 and selectively inhibiting the activity of the CXCL12/HMGB1 heterocomplex. Furthermore, HBP08 binds HMGB1 with the highest affinity reported so far (K_d of 0.8 ± 0.4 μM). The identification of this peptide represents an important step toward the development of innovative pharmacological tools for the treatment of severe chronic inflammatory conditions characterized by an uncontrolled immune response.

Botulinum neurotoxin inhibitor binding dynamics and kinetics relevant for drug design

BACKGROUND

A natural product analog, 3-(4-nitrophenyl)-7H-furo[3,2-g]chromen-7-one, which is a nitrophenyl psoralen (NPP) was found to be an effective inhibitor of botulinum neurotoxin type A (BoNT/A).

METHODS

In this work, we performed enzyme inhibition kinetics and employed biochemical techniques such as isothermal calorimetry (ITC) and fluorescence spectroscopy as well as molecular modeling to examine the kinetics and binding mechanism of NPP inhibitor with BoNT/A LC.

RESULTS

Studies of inhibition mechanism and binding dynamics of NPP to BoNT/A light chain (BoNT/A LC) showed that NPP is a mixed type inhibitor for the zinc endopeptidase activity, implying that at least part of the inhibitor-enzyme binding site may be different from the substrate-enzyme binding site. By using biochemical techniques, we demonstrated NPP forms a stable complex with BoNT/A LC. These observations were confirmed by Molecular Dynamics (MD) simulation, which demonstrates that NPP binds to the site near the active site.

CONCLUSION

The NPP binding interferes with BoNT/A LC binding to the SNAP-25, hence, inhibits its cleavage. Based on these results, we propose a modified strategy for designing a molecule to enhance the efficiency of the inhibition against the neurotoxic effect of BoNT.

GENERAL SIGNIFICANCE

Insights into the interactions of NPP with BoNT/A LC using biochemical and computational approaches will aid in the future development of effective countermeasures and better pharmacological strategies against botulism.

Impact of incorporated drugs on material properties of amorphous solid dispersions

Formulation development of amorphous solid dispersions (ASD) still is challenging although several poorly water-soluble drugs have been marketed using this technique. During development of novel drugs, the selection of the preparation technique and polymer matrix is commonly performed for the certain drug via screening tools. However, if general trends regarding material properties are to be investigated, this approach is not beneficial, although often utilized in literature. The main component of the ASD usually is the polymer and thus it predominantly determines the material properties of the system. Therefore, to study the impact of different drugs and their drug loads on mechanical properties and wettability, three poorly soluble model drugs with drug loads ranging from 10% to 40% were incorporated into copovidone via hot-melt extrusion. The obtained extrudates were subsequently characterized regarding mechanical properties by applying diametral compression test and nanoindentation and the results were compared to the performance during tablet compression. Incorporation of all tested drugs resulted in a similar increase in brittleness of the ASDs, whereas the Young's modulus and hardness changed differently in dependence of the incorporated drug. These observations correlated well with the performance during tablet compression and it was concluded, that the brittleness seemed to be the predominant factor influencing the compression behavior of copovidone-based ASDs. Furthermore, the degree of water absorption and wettability was assessed by applying dynamic vapor sorption experiments and contact angle measurements. Here, the incorporated drugs impacted the contact angle to different degrees and a strong correlation between the contact angle and disintegration time was observable. These results highlight the importance of thorough characterization of the ASDs as it helps to predict their performance during tablet compression and thus facilitates the optimal selection of excipients.

Sampling of the conformational landscape of small proteins with Monte Carlo methods

Computer simulation provides an increasingly realistic picture of large-scale conformational change of proteins, but investigations remain fundamentally constrained by the femtosecond timestep of molecular dynamics simulations. For this reason, many biologically interesting questions cannot be addressed using accessible state-of-the-art computational resources. Here, we report the development of an all-atom Monte Carlo approach that permits the modelling of the large-scale conformational change of proteins using standard off-the-shelf computational hardware and standard all-atom force fields. We demonstrate extensive thermodynamic characterization of the folding process of the α-helical Trp-cage, the Villin headpiece and the β-sheet WW-domain. We fully characterize the free energy landscape, transition states, energy barriers between different states, and the per-residue stability of individual amino acids over a wide temperature range. We demonstrate that a state-of-the-art intramolecular force field can be combined with an implicit solvent model to obtain a high quality of the folded structures and also discuss limitations that still remain.

Molecular dynamics simulation and free energy calculation studies of Coagulin L as dipeptidyl peptidase-4 inhibitor

Plant derived product can be used as other alternatives to currently used drugs for controlling chronic diseases like Diabetes mellitus. The potential of Coagulin L (a constituent of Withania coagulans) as dipeptidyl peptidase-4 (DPP-4) inhibitor was evaluated by molecular modelling study. It was observed that amino acid residues such as Glu205, Glu206, Tyr 547, His 740, and Try662 interacts with Coagulin L and Saxagliptin (a known DPP-4 inhibitor). Other nonbonded interactions of Coagulin L and Saxagliptin with DPP-4 binding residues were also found similar. The docking energy of Coagulin L was found to be -7.69 Kcal/mol whereas -8.44 kcal/mol was recorded for Saxagliptin. MD simulation study revealed stable binding throughout 100 ns simulation. RMSD plot of the complex was stabilized in 43 ns and remained stable during entire simulation(100 ns). RMSF plot of DPP-4 Coagulin L interaction showed major fluctuations at residue 246 and 766, however, Arg 125, Glu 205, Ser 209 and His 740 showed no major perturbations. Principal Component Analysis showed that important dynamics of the protein remain unchanged during entire simulation since the non-polar, van der waals, ionic interaction and solvation energy, altogether play important role in the complex stability. The molecular modelling study of DPP-4 with Coagulin L was an effort to establish correlation with traditional practices of Withania coagulans as antidiabetic agent in Indian subcontinent.Communicated by Ramaswamy H. Sarma.

Botulinum Endopeptidase: SAXS Experiments and MD Simulations Reveal Extended Solution Structures That Account for Its Biochemical Properties

Development of antidotes against botulism requires understanding of the enzymatically active conformations of Botulinum neurotoxin serotype A (BoNT/A) light chain (LCA). We performed small angle X-ray scattering (SAXS) to characterize the solution structures of truncated light chain (tLCA). The 34-37 Å radius of gyration of tLCA was 1.5-times greater than the averaged 22-23-Å radius from the crystal structures. The bimodal distribution of interatomic distances P(r) indicated the two-domain tLCA structure with 129-133 Å size, and Kratky plots indicated the tLCA partial unfolding in the 25-37 °C temperature range. To interpret these data, we employed molecular dynamics simulations and machine learning. Excellent agreement between experimental and theoretical P(r) profiles helped to resolve conformational subpopulations of tLCA in solution. Partial unfolding of the C-terminal portion of tLCA (residues 339-425) results in formation of extended conformations with the larger globular domain (residues 2-298) and the smaller unstructured domain (339-425). The catalytic domain, buried 20 Å-deep inside the crystal structure, becomes accessible in extended solution conformations (8-9 Å deep). The C- and N-termini containing different functional sequence motifs are maximally separated in the extended conformations. Our results offer physical insights into the molecular basis of BoNT/A function and stress the importance of reversible unfolding-refolding transitions and hydrophobic interactions.

The Dependence of Implicit Solvent Model Parameters and Electronic Absorption Spectra and Photoinduced Charge Transfer

In this work, the relationship between multiple solvent parameters and charge transfer index was analyzed by multi-factor multi-variate partial least squares regression (PLSR). The charge transfer of the molecule is visualized by the analysis of the excited state wave function. Hydrogen bond basicity and surface tension can significantly affect charge transfer by studying the solvation model parameters and charge transfer index. Finally, a method in which a solvent regulates charge transfer strength and migration length is proposed.

A grid-based algorithm in conjunction with a gaussian-based model of atoms for describing molecular geometry

A novel grid-based method is presented, which in conjunction with a smooth Gaussian-based model of atoms, is used to compute molecular volume (MV) and surface area (MSA). The MV and MSA are essential for computing nonpolar component of free energies. The objective of our grid-based approach is to identify solute atom pairs that share overlapping volumes in space. Once completed, this information is used to construct a rooted tree using depth-first method to yield the final volume and SA by using the formulations of the Gaussian model described by Grant and Pickup (J. Phys Chem, 1995, 99, 3503). The method is designed to function uninterruptedly with the grid-based finite-difference method implemented in Delphi, a popular and open-source package used for solving the Poisson-Boltzmann equation (PBE). We demonstrate the time efficacy of the method while also validating its performance in terms of the effect of grid-resolution, positioning of the solute within the grid-map and accuracy in identification of overlapping atom pairs. We also explore and discuss different aspects of the Gaussian model with key emphasis on its physical meaningfulness. This development and its future release with the Delphi package are intended to provide a physically meaningful, fast, robust and comprehensive tool for MM/PBSA based free energy calculations. © 2019 Wiley Periodicals, Inc.

Assessing the Accuracy of Different Solvation Models To Describe Protein Adsorption

In protein adsorption, the surrounding solvent has an important role in mediating protein-surface interactions. Therefore, it is of paramount importance that the solvent methods employed to model these kinds of processes are able to correctly capture the complex mechanisms occurring in the protein-water-surface interface. Here, we test the suitability of the two most popular implicit solvent methods based on the Generalized Born formalism to describe the adsorption process of the immunoglobulin G (IgG) on a hydrophobic graphene surface. Our results show that in both cases, IgG experiences an extreme and early (in less than 40 ns) unfolding as a result of the adsorption to the surface in contrast with previous experimental findings. A detailed energy decomposition analysis of explicit and implicit solvent simulations reveals that this discrepancy arises from the ill-characterization of two energy components in implicit solvent methods. These findings help to elucidate how implicit solvent models may be improved to accurately characterize the protein adsorption process.

Alternation of phases of regular and irregular dynamics in protein folding

The regularity of the dynamics in different phases of protein folding is investigated for a set of proteins which undergo a cooperative, two-state folding transition. To determine the degree of regularity of the dynamics, the fractal dimension of probability fluxes is calculated on the basis of simulated folding trajectories. It has been found that the phases of regular and irregular dynamics alternate as follows. In the initial (collapse) phase of folding, the dynamics are essentially regular. Then, as the protein comes to the basin of semicompact states that precedes the transition state, the dynamics become irregular. At the transition state, the dynamics are regularized again but become less regular when the nativelike states are explored. Depending on the specific conditions at which the protein folding was considered, some phases of the dynamics could not be well resolved, but no significant deviation from this general picture has been observed. The regularization of the dynamics at the transition state is discussed in relation to the recent studies of the Hamiltonian dynamics of small clusters, where both regular and chaotic dynamics were observed depending on the flatness of the energy surface at the transition state.

Peptide and Protein Structure Prediction with a Simplified Continuum Solvent Model

A continuum solvent model based on screened Coulomb potentials has been simplified and parametrized to sample native-like structures in replica-exchange simulations of each of six different peptides and miniproteins. Low-energy, native, and non-native structures were used to iteratively refine 11 parameter values. The centroid of the largest cluster of structures sampled in simulations initiated from an extended conformation represents the predicted structure. The main-chain rms deviation of this prediction from the experimental structure was 0.47 Å for the 12-residue Trp-zip2, 0.86 Å for the 14-residue MBH12, 2.53 Å for the 17-residue U(1-17)T9D, 2.03 Å for the 20-residue BS1, 1.08 Å for the 20-residue Trp-cage, and 3.64 Å for the 35-residue villin headpiece subdomain HP35. The centroid of the sixth largest cluster sampled for HP35 deviated by 0.91 Å. The CHARMM22/CMAP force field was used, with an additional ψ torsion term for residues other than glycine and proline. Six parameters govern the dielectric response of the continuum solvent, and four values of surface tension approximate nonpolar effects. An atom's self-energy and interaction energies are screened independently, each depending on whether the atom is part of a charged group, a neutral hydrogen-bonding main-chain group, or any other neutral group. The parameters inferred result in strong main-chain hydrogen bonds, consistent with the view that protein folding is dominated by the formation of these bonds. (1,2) Conformations of MBH12 and BS1 were excluded from the energy-function refinement, suggesting the parameters, referred to as SCP18, are transferable. An efficient estimate of solvent-accessible surface area is also described.

IDeAS: automated design tool for hetero-chiral protein folds

Incorporating D amino acids in the protein design alphabet can in principle multiply the design space by many orders of magnitude. All native proteins are polymers composed of L chiral amino acids. Practically limitless in diversity over amino acid sequences, protein structure is limited in folds and thus shapes, principally due to the poly L stereochemistry of their backbone. To diversify shapes, we introduced both L- and D α-amino acids as design alphabets to explore the possibility of generating novel folds, varied in chemical as well as stereo-chemical sequence. Now, to have stereochemically-defined proteins tuned chemically, we present the Inverse Design and Automation Software, IDeAS. Retro-fitting side chains on a backbone with L and D stereochemistry, the software demonstrate functional fits over stereo-chemically diverse folds in a range of applications of interest in protein design.

Regulatory element in fibrin triggers tension-activated transition from catch to slip bonds

Fibrin formation and mechanical stability are essential in thrombosis and hemostasis. To reveal how mechanical load impacts fibrin, we carried out optical trap-based single-molecule forced unbinding experiments. The strength of noncovalent A:a knob-hole bond stabilizing fibrin polymers first increases with tensile force (catch bonds) and then decreases with force when the force exceeds a critical value (slip bonds). To provide the structural basis of catch-slip-bond behavior, we analyzed crystal structures and performed molecular modeling of A:a knob-hole complex. The movable flap (residues γ295 to γ305) containing the weak calcium-binding site γ2 serves as a tension sensor. Flap dissociation from the B domain in the γ-nodule and translocation to knob 'A' triggers hole 'a' closure, resulting in the increase of binding affinity and prolonged bond lifetimes. The discovery of biphasic kinetics of knob-hole bond rupture is quantitatively explained by using a theory, formulated in terms of structural transitions in the binding pocket between the low-affinity (slip) and high-affinity (catch) states. We provide a general framework to understand the mechanical response of protein pairs capable of tension-induced remodeling of their association interface. Strengthening of the A:a knob-hole bonds at 30- to 40-pN forces might favor formation of nascent fibrin clots subject to hydrodynamic shear in vivo.

Atomic Structural Models of Fibrin Oligomers

The space-filling fibrin network is a major part of clots and thrombi formed in blood. Fibrin polymerization starts when fibrinogen, a plasma protein, is proteolytically converted to fibrin, which self-assembles to form double-stranded protofibrils. When reaching a critical length, these intermediate species aggregate laterally to transform into fibers arranged into branched fibrin network. We combined multiscale modeling in silico with atomic force microscopy (AFM) imaging to reconstruct complete atomic models of double-stranded fibrin protofibrils with γ-γ crosslinking, A:a and B:b knob-hole bonds, and αC regions-all important structural determinants not resolved crystallographically. Structures of fibrin oligomers and protofibrils containing up to 19 monomers were successfully validated by quantitative comparison with high-resolution AFM images. We characterized the protofibril twisting, bending, kinking, and reversibility of A:a knob-hole bonds, and calculated hydrodynamic parameters of fibrin oligomers. Atomic structures of protofibrils provide a basis to understand mechanisms of early stages of fibrin polymerization.

Turbulence in protein folding: Vorticity, scaling and diffusion of probability flows

Recently, when studying folding of a SH3 domain, we discovered that the flows of transitions between protein states can be surprisingly similar to turbulent fluid flows. This similarity was not restricted by a vortex pattern of the flow fields but extended to a spatial correlation of flow fluctuations, resulting, in particular, in the structure functions such as in the Kolmogorov theory of homogeneous and isotropic turbulence. Here, we undertake a detailed analysis of spatial distribution of folding flows and their similarity to turbulent fluid flows. Using molecular dynamics simulations, we study folding of another benchmark system—Trp-cage miniprotein, which has different content of secondary structure elements and mechanism of folding. Calculating the probability fluxes of transitions in a three-dimensional space of collective variables, we have found that similar to the SH3 domain, the structure functions of the second and third orders correspond to the Kolmogorov functions. The spatial distributions of the probability fluxes are self-similar with a fractal dimension, and the fractal index decreases toward the native state, indicating that the flow becomes more turbulent as the native state is approached. We also show that the process of folding can be viewed as Brownian diffusion in the space of probability fluxes. The diffusion coefficient plays a role of the key parameter that defines the structures functions, similar to the rate of dissipation of kinetic energy in hydrodynamic turbulence. The obtained results, first, show that the very complex dynamics of protein folding allows a simple characterization in terms of scaling and diffusion of probability fluxes, and, secondly, they suggest that the turbulence phenomena similar to hydrodynamic turbulence are not specific of folding of a particular protein but are common to protein folding.

Modeling the effects of lattice defects on microtubule breaking and healing

Microtubule reorganization often results from the loss of polymer induced through breakage or active destruction by energy-using enzymes. Pre-existing defects in the microtubule lattice likely lower structural integrity and aid filament destruction. Using large-scale molecular simulations, we model diverse microtubule fragments under forces generated at specific positions to locally crush the filament. We show that lattices with 2% defects are crushed and severed by forces three times smaller than defect-free ones. We validate our results with direct comparisons of microtubule kinking angles during severing. We find a high statistical correlation between the angle distributions from experiments and simulations indicating that they sample the same population of structures. Our simulations also indicate that the mechanical environment of the filament affects breaking: local mechanical support inhibits healing after severing, especially in the case of filaments with defects. These results recall reports of microtubule healing after flow-induced bending and corroborate prior experimental studies that show severing is more likely at locations where microtubules crossover in networks. Our results shed new light on mechanisms underlying the ability of microtubules to be destroyed and healed in the cell, either by external forces or by severing enzymes wedging dimers apart. © 2016 Wiley Periodicals, Inc.

Dynamic Transition from α-Helices to β-Sheets in Polypeptide Coiled-Coil Motifs

We carried out dynamic force manipulations in silico on a variety of coiled-coil protein fragments from myosin, chemotaxis receptor, vimentin, fibrin, and phenylalanine zippers that vary in size and topology of their α-helical packing. When stretched along the superhelical axis, all superhelices show elastic, plastic, and inelastic elongation regimes and undergo a dynamic transition from the α-helices to the β-sheets, which marks the onset of plastic deformation. Using the Abeyaratne-Knowles formulation of phase transitions, we developed a new theoretical methodology to model mechanical and kinetic properties of protein coiled-coils under mechanical nonequilibrium conditions and to map out their energy landscapes. The theory was successfully validated by comparing the simulated and theoretical force-strain spectra. We derived the scaling laws for the elastic force and the force for α-to-β transition, which can be used to understand natural proteins' properties as well as to rationally design novel biomaterials of required mechanical strength with desired balance between stiffness and plasticity.

Temperature evolution of Trp-cage folding pathways: An analysis by dividing the probability flux field into stream tubes

Owing to its small size and very fast folding rate, the Trp-cage miniprotein has become a benchmark system to study protein folding. Two folding pathways were found to be characteristic of this protein: pathway I, in which the hydrophobic collapse precedes the formation of α-helix, and pathway II, in which the events occur in the reverse order. At the same time, the relative contribution of these pathways at different temperatures as well as the nature of transition from one pathway to the other remain unclear. To gain insight into this issue, we employ a recently proposed hydrodynamic description of protein folding, in which the process of folding is considered as a motion of a "folding fluid" (Chekmarev et al., Phys. Rev. Lett. 100(1), 018107 2008). Using molecular dynamics simulations, we determine the field of probability fluxes of transitions in a space of collective variables and divide it into stream tubes. Each tube contains a definite fraction of the total folding flow and can be associated with a certain pathway. Specifically, three temperatures were considered, T = 285K, T = 315K, and T = 325K. We have found that as the temperature increases, the contribution of pathway I, which is approximately 90% of the total folding flow at T = 285K, decreases to approximately 10% at T = 325K, i.e., pathway II becomes dominant. At T = 315K, both pathways contribute approximately equally. All these temperatures are found below the calculated melting point, which suggests that the Trp-cage folding mechanism is determined by kinetic factors rather than thermodynamics.

Efficacy and cytotoxicity in cell culture of novel α-hydroxytropolone inhibitors of hepatitis B virus ribonuclease H

Chronic Hepatitis B virus (HBV) infection is a major worldwide public health problem. Current direct-acting anti-HBV drugs target the HBV DNA polymerase activity, but the equally essential viral ribonuclease H (RNaseH) activity is unexploited as a drug target. Previously, we reported that α-hydroxytropolone compounds can inhibit the HBV RNaseH and block viral replication. Subsequently, we found that our biochemical RNaseH assay underreports efficacy of the α-hydroxytropolones against HBV replication. Therefore, we conducted a structure-activity analysis of 59 troponoids against HBV replication in cell culture. These studies revealed that antiviral efficacy is diminished by larger substitutions on the tropolone ring, identified key components in the substitutions needed for high efficacy, and revealed that cytotoxicity correlates with increased lipophilicity of the α-hydroxytropolones. These data provide key guidance for further optimization of the α-hydroxytropolone scaffold as novel HBV RNaseH inhibitors.

CHARMM-GUI 10 years for biomolecular modeling and simulation

CHARMM-GUI, http://www.charmm-gui.org, is a web-based graphical user interface that prepares complex biomolecular systems for molecular simulations. CHARMM-GUI creates input files for a number of programs including CHARMM, NAMD, GROMACS, AMBER, GENESIS, LAMMPS, Desmond, OpenMM, and CHARMM/OpenMM. Since its original development in 2006, CHARMM-GUI has been widely adopted for various purposes and now contains a number of different modules designed to set up a broad range of simulations: (1) PDB Reader & Manipulator, Glycan Reader, and Ligand Reader & Modeler for reading and modifying molecules; (2) Quick MD Simulator, Membrane Builder, Nanodisc Builder, HMMM Builder, Monolayer Builder, Micelle Builder, and Hex Phase Builder for building all-atom simulation systems in various environments; (3) PACE CG Builder and Martini Maker for building coarse-grained simulation systems; (4) DEER Facilitator and MDFF/xMDFF Utilizer for experimentally guided simulations; (5) Implicit Solvent Modeler, PBEQ-Solver, and GCMC/BD Ion Simulator for implicit solvent related calculations; (6) Ligand Binder for ligand solvation and binding free energy simulations; and (7) Drude Prepper for preparation of simulations with the CHARMM Drude polarizable force field. Recently, new modules have been integrated into CHARMM-GUI, such as Glycolipid Modeler for generation of various glycolipid structures, and LPS Modeler for generation of lipopolysaccharide structures from various Gram-negative bacteria. These new features together with existing modules are expected to facilitate advanced molecular modeling and simulation thereby leading to an improved understanding of the structure and dynamics of complex biomolecular systems. Here, we briefly review these capabilities and discuss potential future directions in the CHARMM-GUI development project. © 2016 Wiley Periodicals, Inc.

Effects from metal ion in tumor endothelial marker 8 and anthrax protective antigen: BioLayer Interferometry experiment and molecular dynamics simulation study

One of the anthrax receptors, tumor endothelial marker 8 (TEM8), is reported to be a potential anticancer target due to its over-expression during tumor angiogenesis. To extend our BioLayer Interferometry study in PA-TEM8 binding, we present a computational approach to reveal the role of an integral metal ion on receptor structure and binding thermodynamics. We estimated the interaction energy between PA and TEM8 using computer simulation. Consistent with experimental study, computational results indicate the metal ion in TEM8 contributes significantly to the binding affinity, and PA-TEM8 binding is more favorable in the presence of Mg²⁺ than Ca²⁺ . Further, computational analysis suggests that the differences in PA-TEM8 binding affinity are comparable to the closely related integrin proteins. The conformation change, which linked to changes in activity of integrins, was not found in TEM8. In the present of Mg²⁺ , TEM8 remains in a conformation analogous to an integrin open (high-affinity) conformation. © 2017 Wiley Periodicals, Inc.

Mechanistic Basis for the Binding of RGD- and AGDV-Peptides to the Platelet Integrin αIIbβ3

Binding of soluble fibrinogen to the activated conformation of the integrin αIIbβ3 is required for platelet aggregation and is mediated exclusively by the C-terminal AGDV-containing dodecapeptide (γC-12) sequence of the fibrinogen γ chain. However, peptides containing the Arg-Gly-Asp (RGD) sequences located in two places in the fibrinogen Aα chain inhibit soluble fibrinogen binding to αIIbβ3 and make substantial contributions to αIIbβ3 binding when fibrinogen is immobilized and when it is converted to fibrin. Here, we employed optical trap-based nanomechanical measurements and computational molecular modeling to determine the kinetics, energetics, and structural details of cyclic RGDFK (cRGDFK) and γC-12 binding to αIIbβ3. Docking analysis revealed that NMR-determined solution structures of cRGDFK and γC-12 bind to both the open and closed αIIbβ3 conformers at the interface between the αIIb β-propeller domain and the β3 βI domain. The nanomechanical measurements revealed that cRGDFK binds to αIIbβ3 at least as tightly as γC-12. A subsequent analysis of molecular force profiles and the number of peptide-αIIbβ3 binding contacts revealed that both peptides form stable bimolecular complexes with αIIbβ3 that dissociate in the 60-120 pN range. The Gibbs free energy profiles of the αIIbβ3-peptide complexes revealed that the overall stability of the αIIbβ3-cRGDFK complex was comparable with that of the αIIbβ3-γC-12 complex. Thus, these results provide a mechanistic explanation for previous observations that RGD- and AGDV-containing peptides are both potent inhibitors of the αIIbβ3-fibrinogen interactions and are consistent with the observation that RGD motifs, in addition to AGDV, support interaction of αIIbβ3 with immobilized fibrinogen and fibrin.

The Levinthal Problem in Amyloid Aggregation: Sampling of a Flat Reaction Space

The formation of amyloid fibrils has been associated with many neurodegenerative disorders, yet the mechanism of aggregation remains elusive, partly because aggregation time scales are too long to probe with atomistic simulations. A microscopic theory of fibril elongation was recently developed that could recapitulate experimental results with respect to the effects of temperature, denaturants, and protein concentration on fibril growth kinetics (Schmit, J. D. J. Chem. Phys. 2013, 138 (18), 185102). The theory identifies the conformational search over H-bonding states as the slowest step in the aggregation process and suggests that this search can be efficiently modeled as a random walk on a rugged one-dimensional energy landscape. This insight motivated the multiscale computational algorithm for simulating fibril growth presented in this paper. Briefly, a large number of short atomistic simulations are performed to compute the system diffusion tensor in the reaction coordinate space predicted by the analytic theory. Ensemble aggregation pathways and growth kinetics are then computed from Markov state model (MSM) trajectories. The algorithm is deployed here to understand the fibril growth mechanism and kinetics of Aβ_16-22 and three of its mutants. The order of growth rates of the wild-type and two single mutation peptides (CHA19 and CHA20) predicted by the MSM trajectories is consistent with experimental results. The simulation also correctly predicts that the double mutation (CHA19/CHA20) would reduce the fibril growth rate, even though the degree of rate reduction with respect to either single mutation is overestimated. This artifact may be attributed to the simplistic implicit solvent model. These trends in the growth rate are not apparent from inspection of the rate constants of individual bonds or the lifetimes of the mis-registered states that are the primary kinetic traps but only emerge in the ensemble of trajectories generated by the MSM.

Heterogeneous dielectric generalized Born model with a van der Waals term provides improved association energetics of membrane-embedded transmembrane helices

The heterogeneous dielectric generalized Born (HDGB) implicit membrane formalism is extended by the addition of a van der Waals dispersion term to better describe the nonpolar components of the free energy of solvation. The new model, termed HDGBvdW, improves the energy estimates in the hydrophobic interior of the membrane, where polar and charged species are rarely found and nonpolar interactions become significant. The implicit van der Waals term for the membrane environment extends the model from Gallicchio et al. (J. Comput. Chem. 2004, 25, 479) by combining separate contributions from each of the membrane components. The HDGBvdW model is validated with a series of test cases ranging from membrane insertion and pair association profiles of amino acid side chain analogs and transmembrane helices. Overall, the HDGBvdW model leads to increased agreement with explicit membrane simulation results and experimental data. © 2016 Wiley Periodicals, Inc.

Automated protein design: Landmarks and operational principles

Protein design has an eventful history spanning over three decades, with handful of success stories reported, and numerous failures not reported. Design practices have benefited tremendously from improvements in computer hardware and advances in scientific algorithms. Though protein folding problem still remains unsolved, the possibility of having multiple sequence solutions for a single fold makes protein design a more tractable problem than protein folding. One of the most significant advancement in this area is the implementation of automated design algorithms on pre-defined templates or completely new folds, optimized through deterministic and heuristic search algorithms. This progress report provides a succinct presentation of important landmarks in automated design attempts, followed by brief account of operational principles in automated design methods.

Predicting the orientation of protein G B1 on hydrophobic surfaces using Monte Carlo simulations

A Monte Carlo algorithm was developed to predict the most likely orientations of protein G B1, an immunoglobulin G (IgG) antibody-binding domain of protein G, adsorbed onto a hydrophobic surface. At each Monte Carlo step, the protein was rotated and translated as a rigid body. The assumption about rigidity was supported by quartz crystal microbalance with dissipation monitoring experiments, which indicated that protein G B1 adsorbed on a polystyrene surface with its native structure conserved and showed that its IgG antibody-binding activity was retained. The Monte Carlo simulations predicted that protein G B1 is likely adsorbed onto a hydrophobic surface in two different orientations, characterized as two mutually exclusive sets of amino acids contacting the surface. This was consistent with sum frequency generation (SFG) vibrational spectroscopy results. In fact, theoretical SFG spectra calculated from an equal combination of the two predicted orientations exhibited reasonable agreement with measured spectra of protein G B1 on polystyrene surfaces. Also, in explicit solvent molecular dynamics simulations, protein G B1 maintained its predicted orientation in three out of four runs. This work shows that using a Monte Carlo approach can provide an accurate estimate of a protein orientation on a hydrophobic surface, which complements experimental surface analysis techniques and provides an initial system to study the interaction between a protein and a surface in molecular dynamics simulations.

Atomistic modelling of scattering data in the Collaborative Computational Project for Small Angle Scattering (CCP-SAS)

The capabilities of current computer simulations provide a unique opportunity to model small-angle scattering (SAS) data at the atomistic level, and to include other structural constraints ranging from molecular and atomistic energetics to crystallography, electron microscopy and NMR. This extends the capabilities of solution scattering and provides deeper insights into the physics and chemistry of the systems studied. Realizing this potential, however, requires integrating the experimental data with a new generation of modelling software. To achieve this, the CCP-SAS collaboration (http://www.ccpsas.org/) is developing open-source, high-throughput and user-friendly software for the atomistic and coarse-grained molecular modelling of scattering data. Robust state-of-the-art molecular simulation engines and molecular dynamics and Monte Carlo force fields provide constraints to the solution structure inferred from the small-angle scattering data, which incorporates the known physical chemistry of the system. The implementation of this software suite involves a tiered approach in which GenApp provides the deployment infrastructure for running applications on both standard and high-performance computing hardware, and SASSIE provides a workflow framework into which modules can be plugged to prepare structures, carry out simulations, calculate theoretical scattering data and compare results with experimental data. GenApp produces the accessible web-based front end termed SASSIE-web, and GenApp and SASSIE also make community SAS codes available. Applications are illustrated by case studies: (i) inter-domain flexibility in two- to six-domain proteins as exemplified by HIV-1 Gag, MASP and ubiquitin; (ii) the hinge conformation in human IgG2 and IgA1 antibodies; (iii) the complex formed between a hexameric protein Hfq and mRNA; and (iv) synthetic 'bottlebrush' polymers.

Label-Free Measurements of Tenofovir Diffusion Coefficients in a Microbicide Gel Using Raman Spectroscopy

Confocal Raman spectroscopy was implemented in a new label-free technique to quantify molecular diffusion coefficients within gels. A leading anti-HIV drug, tenofovir, was analyzed in a clinical microbicide gel. The gel was tested undiluted, and in 10%-50% wt/wt dilutions with vaginal fluid simulant to capture the range of conditions likely occurring in vivo. The concentration distributions of tenofovir in gel over time and space were measured and input to a mathematical diffusion model to deduce diffusion coefficients. These were 3.16 ± 0.11 × 10^-6 cm²/s in undiluted gel, and increased by 11%-46% depending on the extent of dilution. Results were interpreted with respect to traditional release rate measurements in devices such as Franz cells. This comparison highlighted an advantage of our assay in that it characterizes the diffusive barrier within the gel material itself; in contrast, release rate in the traditional assay is affected by external conditions, such as drug partitioning at the gel/liquid sink interface. This new assay is relevant to diffusion in polymeric hydrogels over pharmacologically relevant length scales, for example, those characteristic of topical drug delivery. Resulting transport parameters are salient measures of drug delivery potential, and serve as inputs to computational models of drug delivery performance.

Molecular investigations into the mechanics of a muscle anchoring complex

The titin-telethonin complex, essential for anchoring filaments in the Z-disk of the sarcomere, is composed of immunoglobulin domains. Surprisingly, atomic force microscopy experiments showed that it resists forces much higher than the typical immunoglobulin domain and that the force distribution is unusually broad. To investigate the origin of this behavior, we developed a multiscale simulation approach, combining minimalist and atomistic models (SOP-AT). By following the mechanical response of the complex on experimental timescales, we found that the mechanical stability of titin-telethonin is modulated primarily by the strength of contacts between telethonin and the two titin chains, and secondarily by the timescales of conformational excursions inside telethonin and the pulled titin domains. Importantly, the conformational transitions executed by telethonin in simulations support its proposed role in mechanosensing. Our SOP-AT computational approach thus provides a powerful tool for the exploration of the link between conformational diversity and the broadness of the mechanical response, which can be applied to other multidomain complexes.

NANOGOLD decorated by pHLIP peptide: comparative force field study

The potential of gold nanoparticles (AuNPs) in therapeutic and diagnostic cancer applications is becoming increasingly recognized, which focuses on their efficient and specific delivery from passive accumulation in tumour tissue to directly targeting tumor-specific biomarkers. AuNPs functionalized by pH low insertion peptide (pHLIP) have recently revealed the capability of targeting acidic tissues and inserting into cell membranes. However, the structure of AuNP-pHLIP conjugates and fundamental gold-peptide interactions still remain unknown. In this study, we have developed a series of molecular dynamics (MD) models reproducing a small gold nanoparticle coupled to pHLIP. We focus on Au135 nanoparticles that comprise a nearly spherical Au core (diameter ∼ 1.4 nm) functionalized with a monomaleimide moiety, mimicking a commercially available monomaleimido NANOGOLD® labelling agent. To probe the structure and folding of pHLIP, which is attached covalently to the maleimide NANOGOLD particle, we have benchmarked the performances of a series of popular, all-atom force fields (FF), including those of OPLS-AA, AMBER03, three variations of CHARMM FFs, as well as united-atom GROMOS G53A6 FF. We found that CHARMMs and OPLSAA FFs predict that in an aqueous salt solution at a neutral pH, pHLIP is partially bound onto the gold surface through some short hydrophobic peptide stretches, while at the same time, a large portion of peptide remains in solution. In contrast, AMBER03 and G53A6 FFs revealed the formation of compact, tightly bound peptide configurations adsorbed onto the nanoparticle core. To reproduce the experimental physical picture of the peptide adsorption onto gold in unfolded and unstructured conformations, our study suggests CHARMM36 and OPLS-AA FFs as a tool of choice for the computational studies of NANOGOLD decorated by pHLIP.

Evaluating the dynamics and electrostatic interactions of folded proteins in implicit solvents

Three implicit solvent models, namely GBMVII, FACTS, and SCPISM, were evaluated for their abilities to emulate an explicit solvent environment by comparing the simulated conformational ensembles, dynamics, and electrostatic interactions of the Src SH2 domain and the Lyn kinase domain. This assessment in terms of structural features in folded proteins expands upon the use of hydration energy as a metric for comparison. All-against-all rms coordinate deviation, average positional fluctuations, and ion-pair distance distribution were used to compare the implicit solvent models with the TIP3P explicit solvent model. Our study shows that the Src SH2 domains solvated with TIP3P, GBMVII, and FACTS sample similar global conformations. Additionally, the Src SH2 ion-pair distance distributions of solvent-exposed side chains corresponding to TIP3P, GBMVII, and FACTS do not differ substantially, indicating that GBMVII and FACTS are capable of modeling these electrostatic interactions. The ion-pair distance distributions of SCPISM are distinct from others, demonstrating that these electrostatic interactions are not adequately reproduced with the SCPISM model. On the other hand, for the Lyn kinase domain, a non-globular protein with bilobal structure and a large concavity on the surface, implicit solvent does not accurately model solvation to faithfully reproduce partially buried electrostatic interactions and lobe-lobe conformations. Our work reveals that local structure and dynamics of small, globular proteins are modeled well using FACTS and GBMVII. Nonetheless, global conformations and electrostatic interactions in concavities of multi-lobal proteins resulting from simulations with implicit solvent models do not match those obtained from explicit water simulations.